| :mod:`functools` --- Higher-order functions and operations on callable objects |
| ============================================================================== |
| |
| .. module:: functools |
| :synopsis: Higher-order functions and operations on callable objects. |
| .. moduleauthor:: Peter Harris <scav@blueyonder.co.uk> |
| .. moduleauthor:: Raymond Hettinger <python@rcn.com> |
| .. moduleauthor:: Nick Coghlan <ncoghlan@gmail.com> |
| .. sectionauthor:: Peter Harris <scav@blueyonder.co.uk> |
| |
| **Source code:** :source:`Lib/functools.py` |
| |
| -------------- |
| |
| The :mod:`functools` module is for higher-order functions: functions that act on |
| or return other functions. In general, any callable object can be treated as a |
| function for the purposes of this module. |
| |
| The :mod:`functools` module defines the following functions: |
| |
| .. function:: cmp_to_key(func) |
| |
| Transform an old-style comparison function to a key function. Used with |
| tools that accept key functions (such as :func:`sorted`, :func:`min`, |
| :func:`max`, :func:`heapq.nlargest`, :func:`heapq.nsmallest`, |
| :func:`itertools.groupby`). This function is primarily used as a transition |
| tool for programs being converted from Python 2 which supported the use of |
| comparison functions. |
| |
| A comparison function is any callable that accept two arguments, compares them, |
| and returns a negative number for less-than, zero for equality, or a positive |
| number for greater-than. A key function is a callable that accepts one |
| argument and returns another value indicating the position in the desired |
| collation sequence. |
| |
| Example:: |
| |
| sorted(iterable, key=cmp_to_key(locale.strcoll)) # locale-aware sort order |
| |
| .. versionadded:: 3.2 |
| |
| |
| .. decorator:: lru_cache(maxsize=128, typed=False) |
| |
| Decorator to wrap a function with a memoizing callable that saves up to the |
| *maxsize* most recent calls. It can save time when an expensive or I/O bound |
| function is periodically called with the same arguments. |
| |
| Since a dictionary is used to cache results, the positional and keyword |
| arguments to the function must be hashable. |
| |
| If *maxsize* is set to None, the LRU feature is disabled and the cache can |
| grow without bound. The LRU feature performs best when *maxsize* is a |
| power-of-two. |
| |
| If *typed* is set to True, function arguments of different types will be |
| cached separately. For example, ``f(3)`` and ``f(3.0)`` will be treated |
| as distinct calls with distinct results. |
| |
| To help measure the effectiveness of the cache and tune the *maxsize* |
| parameter, the wrapped function is instrumented with a :func:`cache_info` |
| function that returns a :term:`named tuple` showing *hits*, *misses*, |
| *maxsize* and *currsize*. In a multi-threaded environment, the hits |
| and misses are approximate. |
| |
| The decorator also provides a :func:`cache_clear` function for clearing or |
| invalidating the cache. |
| |
| The original underlying function is accessible through the |
| :attr:`__wrapped__` attribute. This is useful for introspection, for |
| bypassing the cache, or for rewrapping the function with a different cache. |
| |
| An `LRU (least recently used) cache |
| <http://en.wikipedia.org/wiki/Cache_algorithms#Least_Recently_Used>`_ works |
| best when the most recent calls are the best predictors of upcoming calls (for |
| example, the most popular articles on a news server tend to change each day). |
| The cache's size limit assures that the cache does not grow without bound on |
| long-running processes such as web servers. |
| |
| Example of an LRU cache for static web content:: |
| |
| @lru_cache(maxsize=20) |
| def get_pep(num): |
| 'Retrieve text of a Python Enhancement Proposal' |
| resource = 'http://www.python.org/dev/peps/pep-%04d/' % num |
| try: |
| with urllib.request.urlopen(resource) as s: |
| return s.read() |
| except urllib.error.HTTPError: |
| return 'Not Found' |
| |
| >>> for n in 8, 290, 308, 320, 8, 218, 320, 279, 289, 320, 9991: |
| ... pep = get_pep(n) |
| ... print(n, len(pep)) |
| |
| >>> print(get_pep.cache_info()) |
| CacheInfo(hits=3, misses=8, maxsize=20, currsize=8) |
| |
| Example of efficiently computing |
| `Fibonacci numbers <http://en.wikipedia.org/wiki/Fibonacci_number>`_ |
| using a cache to implement a |
| `dynamic programming <http://en.wikipedia.org/wiki/Dynamic_programming>`_ |
| technique:: |
| |
| @lru_cache(maxsize=None) |
| def fib(n): |
| if n < 2: |
| return n |
| return fib(n-1) + fib(n-2) |
| |
| >>> print([fib(n) for n in range(16)]) |
| [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610] |
| |
| >>> print(fib.cache_info()) |
| CacheInfo(hits=28, misses=16, maxsize=None, currsize=16) |
| |
| .. versionadded:: 3.2 |
| |
| .. versionchanged:: 3.3 |
| Added the *typed* option. |
| |
| .. decorator:: total_ordering |
| |
| Given a class defining one or more rich comparison ordering methods, this |
| class decorator supplies the rest. This simplifies the effort involved |
| in specifying all of the possible rich comparison operations: |
| |
| The class must define one of :meth:`__lt__`, :meth:`__le__`, |
| :meth:`__gt__`, or :meth:`__ge__`. |
| In addition, the class should supply an :meth:`__eq__` method. |
| |
| For example:: |
| |
| @total_ordering |
| class Student: |
| def __eq__(self, other): |
| return ((self.lastname.lower(), self.firstname.lower()) == |
| (other.lastname.lower(), other.firstname.lower())) |
| def __lt__(self, other): |
| return ((self.lastname.lower(), self.firstname.lower()) < |
| (other.lastname.lower(), other.firstname.lower())) |
| |
| .. versionadded:: 3.2 |
| |
| |
| .. function:: partial(func, *args, **keywords) |
| |
| Return a new :class:`partial` object which when called will behave like *func* |
| called with the positional arguments *args* and keyword arguments *keywords*. If |
| more arguments are supplied to the call, they are appended to *args*. If |
| additional keyword arguments are supplied, they extend and override *keywords*. |
| Roughly equivalent to:: |
| |
| def partial(func, *args, **keywords): |
| def newfunc(*fargs, **fkeywords): |
| newkeywords = keywords.copy() |
| newkeywords.update(fkeywords) |
| return func(*(args + fargs), **newkeywords) |
| newfunc.func = func |
| newfunc.args = args |
| newfunc.keywords = keywords |
| return newfunc |
| |
| The :func:`partial` is used for partial function application which "freezes" |
| some portion of a function's arguments and/or keywords resulting in a new object |
| with a simplified signature. For example, :func:`partial` can be used to create |
| a callable that behaves like the :func:`int` function where the *base* argument |
| defaults to two: |
| |
| >>> from functools import partial |
| >>> basetwo = partial(int, base=2) |
| >>> basetwo.__doc__ = 'Convert base 2 string to an int.' |
| >>> basetwo('10010') |
| 18 |
| |
| |
| .. function:: reduce(function, iterable[, initializer]) |
| |
| Apply *function* of two arguments cumulatively to the items of *sequence*, from |
| left to right, so as to reduce the sequence to a single value. For example, |
| ``reduce(lambda x, y: x+y, [1, 2, 3, 4, 5])`` calculates ``((((1+2)+3)+4)+5)``. |
| The left argument, *x*, is the accumulated value and the right argument, *y*, is |
| the update value from the *sequence*. If the optional *initializer* is present, |
| it is placed before the items of the sequence in the calculation, and serves as |
| a default when the sequence is empty. If *initializer* is not given and |
| *sequence* contains only one item, the first item is returned. |
| |
| |
| .. function:: update_wrapper(wrapper, wrapped, assigned=WRAPPER_ASSIGNMENTS, updated=WRAPPER_UPDATES) |
| |
| Update a *wrapper* function to look like the *wrapped* function. The optional |
| arguments are tuples to specify which attributes of the original function are |
| assigned directly to the matching attributes on the wrapper function and which |
| attributes of the wrapper function are updated with the corresponding attributes |
| from the original function. The default values for these arguments are the |
| module level constants *WRAPPER_ASSIGNMENTS* (which assigns to the wrapper |
| function's *__name__*, *__module__*, *__annotations__* and *__doc__*, the |
| documentation string) and *WRAPPER_UPDATES* (which updates the wrapper |
| function's *__dict__*, i.e. the instance dictionary). |
| |
| To allow access to the original function for introspection and other purposes |
| (e.g. bypassing a caching decorator such as :func:`lru_cache`), this function |
| automatically adds a __wrapped__ attribute to the wrapper that refers to |
| the original function. |
| |
| The main intended use for this function is in :term:`decorator` functions which |
| wrap the decorated function and return the wrapper. If the wrapper function is |
| not updated, the metadata of the returned function will reflect the wrapper |
| definition rather than the original function definition, which is typically less |
| than helpful. |
| |
| :func:`update_wrapper` may be used with callables other than functions. Any |
| attributes named in *assigned* or *updated* that are missing from the object |
| being wrapped are ignored (i.e. this function will not attempt to set them |
| on the wrapper function). :exc:`AttributeError` is still raised if the |
| wrapper function itself is missing any attributes named in *updated*. |
| |
| .. versionadded:: 3.2 |
| Automatic addition of the ``__wrapped__`` attribute. |
| |
| .. versionadded:: 3.2 |
| Copying of the ``__annotations__`` attribute by default. |
| |
| .. versionchanged:: 3.2 |
| Missing attributes no longer trigger an :exc:`AttributeError`. |
| |
| |
| .. decorator:: wraps(wrapped, assigned=WRAPPER_ASSIGNMENTS, updated=WRAPPER_UPDATES) |
| |
| This is a convenience function for invoking ``partial(update_wrapper, |
| wrapped=wrapped, assigned=assigned, updated=updated)`` as a function decorator |
| when defining a wrapper function. For example: |
| |
| >>> from functools import wraps |
| >>> def my_decorator(f): |
| ... @wraps(f) |
| ... def wrapper(*args, **kwds): |
| ... print('Calling decorated function') |
| ... return f(*args, **kwds) |
| ... return wrapper |
| ... |
| >>> @my_decorator |
| ... def example(): |
| ... """Docstring""" |
| ... print('Called example function') |
| ... |
| >>> example() |
| Calling decorated function |
| Called example function |
| >>> example.__name__ |
| 'example' |
| >>> example.__doc__ |
| 'Docstring' |
| |
| Without the use of this decorator factory, the name of the example function |
| would have been ``'wrapper'``, and the docstring of the original :func:`example` |
| would have been lost. |
| |
| |
| .. _partial-objects: |
| |
| :class:`partial` Objects |
| ------------------------ |
| |
| :class:`partial` objects are callable objects created by :func:`partial`. They |
| have three read-only attributes: |
| |
| |
| .. attribute:: partial.func |
| |
| A callable object or function. Calls to the :class:`partial` object will be |
| forwarded to :attr:`func` with new arguments and keywords. |
| |
| |
| .. attribute:: partial.args |
| |
| The leftmost positional arguments that will be prepended to the positional |
| arguments provided to a :class:`partial` object call. |
| |
| |
| .. attribute:: partial.keywords |
| |
| The keyword arguments that will be supplied when the :class:`partial` object is |
| called. |
| |
| :class:`partial` objects are like :class:`function` objects in that they are |
| callable, weak referencable, and can have attributes. There are some important |
| differences. For instance, the :attr:`__name__` and :attr:`__doc__` attributes |
| are not created automatically. Also, :class:`partial` objects defined in |
| classes behave like static methods and do not transform into bound methods |
| during instance attribute look-up. |
| |